First International Conference on Autonomic Computing (ICAC'04)
Autonomic Self-Optimization According to Business Objectives
New York, New York
May 17-May 18
ISBN: 0-7695-2114-2
A central challenge in the runtime management of computing environments is the necessity to keep these environments continuously optimized. In this paper we introduce a new paradigm, which focuses on self-optimization according to high-level business objectives such as maximizing revenues. It replaces the more traditional optimizations that are based upon IT measures such as resource availability. A general, autonomous process is defined to enable such optimizations, and a set of technologies and methodologies is introduced to support the implementation of such a process. The paper concludes with two types of validation tests carried out on an eCommerce site, that demonstrate the value and applicability of this approach.
Citation:
Sarel Aiber, Dagan Gilat, Ariel Landau, Natalia Razinkov, Aviad Sela, Segev Wasserkrug, "Autonomic Self-Optimization According to Business Objectives," icac, pp.206-213, First International Conference on Autonomic Computing (ICAC'04), 2004